__all__ = ["render_surface_function"]
import os
import warnings
import skimage.measure
import webcolors as wc
from ..registration import resample_image
try:
import chart_studio.plotly as py
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
from plotly.graph_objs import *
from plotly import figure_factory as FF
except:
warnings.warn(
"Cant import Plotly. Install it `pip install chart_studio` if you want to use ants.render_surface_function"
)
[docs]def render_surface_function(
surfimg,
funcimg=None,
alphasurf=0.2,
alphafunc=1.0,
isosurf=0.5,
isofunc=0.5,
smoothsurf=None,
smoothfunc=None,
cmapsurf="grey",
cmapfunc="red",
filename=None,
notebook=False,
auto_open=False,
):
"""
Render an image as a base surface and an optional collection of other image.
ANTsR function: `renderSurfaceFunction`
NOTE: The ANTsPy version of this function is actually completely different
than the ANTsR version, although they should produce similar results.
Arguments
---------
surfimg : ANTsImage
Input image to use as rendering substrate.
funcimg : ANTsImage
Input list of images to use as functional overlays.
alphasurf : scalar
alpha for the surface contour
alphafunc : scalar
alpha value for functional blobs
isosurf : scalar
intensity level that defines lower threshold for surface image
isofunc : scalar
intensity level that defines lower threshold for functional image
smoothsurf : scalar (optional)
smoothing for the surface image
smoothfunc : scalar (optional)
smoothing for the functional image
cmapsurf : string
color map for surface image
cmapfunc : string
color map for functional image
filename : string
where to save rendering. if None, will plot interactively
notebook : boolean
whether you're in a jupyter notebook.
Returns
-------
N/A
Example
-------
>>> import ants
>>> mni = ants.image_read(ants.get_ants_data('mni'))
>>> mnia = ants.image_read(ants.get_ants_data('mnia'))
>>> ants.render_surface_function(mni, mnia, alphasurf=0.1, filename='/users/ncullen/desktop/surffnc.png')
"""
cmap_dict = {
"grey": "Greys",
"gray": "Greys",
"red": "Reds",
"green": "Greens",
"jet": "Jet",
}
if surfimg.dimension != 3:
raise ValueError("surfimg must be 3D")
# if (filename is None) and (not notebook_render):
# raise Exception('Must either 1) give filename, 2) set `html_render`=True or 3) set `notebook_render`=True')
if notebook:
init_notebook_mode(connected=True)
fig_list = []
fig_data_list = []
surfimg = resample_image(surfimg, (3, 3, 3))
surfimg_arr = surfimg.numpy()
surfverts, surffaces, _, _ = skimage.measure.marching_cubes_lewiner(
surfimg_arr, isosurf, spacing=(1, 1, 1)
)
surffig = FF.create_trisurf(
x=surfverts[:, 0],
y=surfverts[:, 1],
z=surfverts[:, 2],
colormap=cmap_dict.get(cmapsurf, cmapsurf),
plot_edges=False,
simplices=surffaces,
)
surffig["data"][0].update(opacity=alphasurf)
fig_list.append(surffig)
fig_data_list.append(surffig.data[0])
if funcimg is not None:
if not isinstance(funcimg, (tuple, list)):
funcimg = [funcimg]
if not isinstance(alphafunc, (tuple, list)):
alphafunc = [alphafunc] * len(funcimg)
if not isinstance(isofunc, (tuple, list)):
isofunc = [isofunc] * len(funcimg)
if not isinstance(cmapfunc, (tuple, list)):
cmapfunc = [cmapfunc] * len(funcimg)
# cmapfunc = [cmap_dict.get(c,c) for c in cmapfunc]
for i in range(len(cmapfunc)):
cmapfunc[i] = "rgb%s" % str(wc.name_to_rgb(cmapfunc[i]))
cmapfunc[i] = [cmapfunc[i]] * 2
for func_idx, fimg in enumerate(funcimg):
if fimg.dimension != 3:
raise ValueError("all funcimgs must be 3D")
fimg = resample_image(fimg, (3, 3, 3))
funcimg_arr = fimg.numpy()
funcverts, funcfaces, _, _ = skimage.measure.marching_cubes_lewiner(
funcimg_arr, isofunc[func_idx], spacing=(1, 1, 1)
)
funcfig = FF.create_trisurf(
x=funcverts[:, 0],
y=funcverts[:, 1],
z=funcverts[:, 2],
plot_edges=False,
simplices=funcfaces,
colormap=cmapfunc[func_idx],
)
funcfig["data"][0].update(opacity=alphafunc[func_idx])
fig_list.append(funcfig)
fig_data_list.append(funcfig.data[0])
if filename is not None:
save_file = "png"
image_filename = filename
filename = image_filename.split(".")[0] + ".html"
else:
image_filename = "ants_plot"
filename = "ants_plot.html"
save_file = None
try:
plot(
fig_data_list,
image=save_file,
filename=filename,
image_filename=image_filename,
auto_open=auto_open,
)
except PermissionError:
print(
"PermissionError caught - are you running jupyter console? Try launching it with sudo privledges (e.g. `sudo jupyter-console`)"
)
